Preliminary Review Copy

PRELIMINARY REVIEW COPY

Technical Report Documentation Page

1. Report No.
0-4013-1 / 2. Government Accession No. / 3. Recipient’s Catalog No.
4. Title and Subtitle
DECISION SUPPORT FRAMEWORK FOR THE EVALUATION OF MODAL COMPETITIVENESS / 5. Report Date
October 31, 2004
6. Performing Organization Code
7. Author(s)
Chandra Bhat, Jolanda Prozzi, Michalis Xyntarakis, Sivaramakrishnan Srinivasan / 8. Performing Organization Report No.
0-4013-1
9. Performing Organization Name and Address
Center for Transportation Research
The University of Texas at Austin
3208 Red River, Suite 200
Austin, TX78705-2650 / 10. Work Unit No. (TRAIS)
11. Contract or Grant No.
0-4013
12. Sponsoring Agency Name and Address
Texas Department of Transportation
Research and Technology Implementation Office
P.O. Box 5080
Austin, TX78763-5080 / 13. Type of Report and Period Covered
Project Report (9/02–10/04)
14. Sponsoring Agency Code
15. Supplementary Notes
Project conducted in cooperation with the U.S. Department of Transportation,
Federal Highway Administration, and the Texas Department of Transportation.
16. Abstract
This report contains the results of research into the development of a decision support system (DSS) aimed to supplement a systematic ongoing process of strategic evaluation and transportation planning at the statewide and metropolitan levels. Specifically, it is intended to provide TxDOT with a forecasting methodology to qualitatively and quantitatively anticipate changes in modal utilization for intercity freight movements and intracity passenger movements. Presented as a prototype software program, it incorporates the results of recent research on the determinants of mode choice as well as lessons learned in practice regarding the effect of specific policies on mode utilization. The software, which was developed as a relational database in MS Access, comprises a qualitative and a quantitative component. The qualitative component can be utilized to examine the direction of the likely impact of a specific factor on mode utilization as well as to find those factors for which a desired change in modal utilization occurs. The quantitative tool contains interactive charts built from public and private databases that allow the analyst to explore multiple aspects of the data and a freight mode choice model developed for Texas that facilitates custom scenario generation and evaluation. Integrated in the qualitative tool is a prototype Delphifreight expert panel survey conducted by the study team to enhance the knowledge base incorporated in the software.
17. Key Words
Passenger mode choice, freight mode choice, decision support system, policy evaluation / 18. Distribution Statement
No restrictions. This document is available to the public through the National Technical Information Service, Springfield, Virginia22161.
19. Security Classif. (of report)
Unclassified / 20. Security Classif. (of this page)
Unclassified / 21. No. of pages
44 / 22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

Decision Support Framework For The Evaluation Of Modal Competitiveness

Chandra Bhat

Jolanda Prozzi

Michalis Xyntarakis

Sivaramakrishnan Srinivasan

CTR Research Report: / 0-4013-1
Report Date: / October 31, 2004
Research Project: / 0-4013
Research Project Title / Competitiveness of Alternative Transportation Modes

Center for Transportation Research

The University of Texas at Austin

3208 Red River

Austin, TX78705

Copyright (c) 2005

Center for Transportation Research

The University of Texas at Austin

All rights reserved

Printed in the United States of America

Disclaimers

Author’s Disclaimer: The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official view or policies of the Federal Highway Administration or the Texas Department of Transportation (TxDOT). This report does not constitute a standard, specification, or regulation.

Patent Disclaimer: There was no invention or discovery conceived or first actually reduced to practice in the course of or under this contract, including any art, method, process, machine manufacture, design or composition of matter, or any new useful improvement thereof, or any variety of plant, which is or may be patentable under the patent laws of the United States of America or any foreign country.

Notice: The United States Government and the State of Texas do not endorse products or manufacturers. If trade or manufacturers’ names appear herein, it is solely because they are considered essential to the object of this report.

Engineering Disclaimer

NOT INTENDED FOR CONSTRUCTION, BIDDING, OR PERMIT PURPOSES.

Project Engineer: Dr. Chandra Bhat

ProfessionalEngineerLicenseState and Number: Texas No. 88971

P. E. Designation: Research Supervisor

Acknowledgments

The authors wish to acknowledge the involvement and direction of the Texas Department of Transportation Project Monitoring Committee, which includes Project Director Ron Hagquist (TPP), Project Coordinator Maria Burke (DES), and the project monitoring committee members. Special thanks are also owed to Aswani Yeraguntla and Sudeshna Sen for all their efforts in developing and populating the Decision Support System.

Table of Contents

1. Introduction

2. Overview of the Decision Support System

2.1 Structure of the DSS

2.1.1 Qualitative Assessment

2.1.2 Quantitative Assessment

2.2 Scope of the Research

2.3 Software Structure and Capabilities

2.4 Concluding Remarks

3. The Qualitative Analysis Tool

3.1 Objective-Oriented Analysis

3.2 Policy-Oriented Analysis

3.3 Concluding Remarks

4. The Delphi Expert Panel Survey

4.1 An Overview of the Delphi Survey

4.2 Application of the Delphi Technique

4.2.1 Survey Questionnaire Design

4.2.2 Expert Panel

4.2.3 Survey Administration

4.2.4 Strengths and Weaknesses

4.3 Incorporating the Survey Results within the DSS

4.4 Concluding Remarks

5. The Quantitative Analysis Tool

5.1 The Baseline Assessment Component

5.1.1 Baseline Assessment for Passenger Traffic

5.1.2 Baseline Assessment for Freight Traffic

5.2 The Freight Mode Choice Prediction Model

5.2.1 The freight mode choice model

5.2.2 Model implementation for predicting more shares

6. Conclusions and Recommendations

References

Appendix A

List of Figures

Figure 3.1Sample output display for objective-oriented analysis

Figure 3.2Sample output display for policy-oriented analysis

Figure 4.1Sample output display for a query on the impact of a specific policy action

Figure 4.2Sample output display for a query on section summary

Figure 5.1Sample pivot chart output for passenger traffic baseline assessment

Figure 5.2Sample pivot chart output for freight traffic baseline assessment

Figure 5.3Input screen for freight mode choice forecasting

Figure 5.4Input screen for scenario definition

Figure 5.5Output charts for the base case and the future year scenario

List of Tables

Table 2.1Modal classifications for passenger and freight travel

Table 2.2Qualitative and quantitative analyses that can be performed using the DSS

Table 3.1Primary factors for passenger and freight transport

Table 3.2List of factors supported by the DSS for passenger traffic

Table 3.3List of factors supported by the DSS for freight traffic

Table 4.1Sample survey questions and response alternatives

Table 5.1List of tables and charts available for passenger traffic baseline assessment

Table 5.2List of tables and charts available for passenger traffic baseline assessment

Table 5.3The fraction split model for freight mode choice

1

1. Introduction

Texas, like other parts of the world, is experiencing changes in social, demographic, economic, land use, and technological patterns that are likely to change the characteristics of passenger and freight travel demand in the state over the next twenty years and beyond. Although many of the factors driving these changes are not directly related to the provision of transportation infrastructure, the manner in which these factors impact the transportation system and its users depends significantly on the actions taken by transportation planning agencies and private stakeholders in the provision and management of transportation systems.

Of particular importance to the Texas Department of Transportation (TxDOT) and to regional and metropolitan transportation planning agencies is the relative importance that different modes of transportation will—and to some extent could or should—play in meeting the mobility needs of the state’s residents and businesses. Over time, the relative competitiveness of specific modes of transportation has changed, as newer technologies have been introduced and as spatial and temporal activity patterns that drive the demand for transportation changed. For example, since the 1950s the use of transit has declined as commuters have shifted to automobiles and have made residential location choices on the basis of automobile accessibility. In addition, over the past decades freight truck traffic has increasedmore rapidly than passenger traffic at a time when building additional road capacity has become more and more expensive and in many cases undesirable. As a result, highway congestion has increased dramatically, resulting in concerns about environmental and energy impacts.

Decision-makers have thus become increasingly concerned about the negative impacts associated with the growing disparity between transportation demand and capacity. It is therefore essential that TxDOT and metropolitan planning agencies adopt an anticipatory role to accommodate future needs in a way that achieves the sustainable, balanced utilization of alternative modes. In an effort to act proactively, TxDOT has contracted with The University of Texas at Austin’s Center for Transportation Research to explore the competitiveness of alternative transportation modes. Specifically, the study’s main objective is to document those factors and policies that have a significant impact on freight and passenger mode shares. To achieve this objective, the research team has developed a decisionsupport system (DSS) to assist TxDOT and local metropolitan planning agencies in planning for an efficient and balanced multi-modal transportation system for Texas.

This report provides an overview of the DSS and includes examples of its use. Chapter 2 discusses the DSS in general and provides an overview of its structure, scope, and capabilities. Chapter 3 describes the qualitative assessment component of the DSS in detail and describes its two major functions: objective- and policy-oriented analysis. Chapter 4 describes the Delphi survey conducted as part of this research to enhance the freight-related knowledge base. Chapter 5 presents the quantitative assessment component of the DSS, which enables the user to undertake baseline assessments and freight mode share forecasting. Finally, Chapter 5 presents the main conclusions and recommendations of this research.

2. Overview of the Decision Support System

This chapter of the report provides an overview of the decision support system (DSS) developed to assist the Texas Department of Transportation (TxDOT) with their multi-modal passenger and freight transportation planning process. The overall intent in the development of the DSS was to provide a comprehensive and easy-to-use knowledge base to study the competitiveness of alternative modes for passenger and freight transportation. Section 2.1 describes the structure of the DSS. Section 2.2 identifies the scope of the research, and Section 2.3 discusses the software structure and capabilities.

2.1Structure of the DSS

The DSS is structured to provide a comprehensive and integrated framework for undertaking both qualitative and quantitative assessments of freight and passenger modal competitiveness. The qualitative analysis component of the DSS is discussed in Section 2.1.1, and the quantitative analysis component is described in Section 2.1.2.

2.1.1Qualitative Assessment

The qualitative assessment component of the DSS is structured to provide the analyst with a comprehensive knowledge base of past research on passenger and freight modeshares and with lessons learned in practice. The knowledge base for passenger travel mode shares is drawn predominantly from published literature. The knowledge base for freight mode shares incorporates expert opinions obtained from a Delphi survey (see Chapter 4 for further details) in addition to published research literature. The need to consult freight experts was motivated by the relative lack of research in this area. The analyst can utilize this knowledge repository in two ways: (1) by undertaking an objective-oriented analysis (i.e., identifying policies and trends that can produce desired modal shifts), and (2) by performing a policy-oriented analysis (i.e., querying the ceteris paribus impacts of policies on mode shares). The qualitative assessment capabilities provided by the DSS software is described in detail in Chapter 3.

2.1.2Quantitative Assessment

Qualitative assessments provide useful indications of the directional impacts of various policy actions on the mode shares, but they do not provide the analyst with a sense of the magnitude of these impacts. The second major component of the DSS, the quantitative assessment component, is intended to provide the analyst with quantitative data in terms of mode shares and socioeconomic trends. Toward that end, this component comprises two features: (1) a database comprising longitudinal data on mode shares, aggregate performance measures, and useful socioeconomic indicators compiled from several data sources, and (2) a mode choice model for predicting future freight mode shares. Although the longitudinal database provides the analyst with useful information on the current modal shares and historical mode-share trends (querying this data is referred to as baseline assessment), the mode choice model helps the user forecast truck and rail mode shares under different socioeconomic scenarios. The quantitative assessment capabilities of the DSS software are described in detail in Chapter 5.

2.2Scope of the Research

The overall objective of this research project was to develop a DSS that can assist planners with both passenger and freight transportation planning. Within the context of passenger transportation, the analysis is restricted to intracity travel, whereas in the case of freight transportation the focus has been on intercity movements. The modal classification adopted for passenger and freight movements are summarized in Table 2.1.

Table 2.1Modal classifications for passenger and freight travel

Passenger / Freight
Intracity Travel / Drive alone / Not applicable
Shared ride
Bus
Nonmotorized (walk and bike)
Intercity Travel / Not applicable / Truck
Rail
Water
Air

In the quantitative analysis component, a mode choice model has been embedded to analyze truck and rail mode share for the freight sector. The inability to embed corresponding mode choice models for passenger flows was dictated by data constraints and software limitations.

2.3Software Structure and Capabilities

The prototype DSSwas developed as a software program in Microsoft Access. Structurally, the software comprises two major components: (1) the knowledge base and (2) the graphical user interface. The knowledge base forms the core of the DSS software and includes the following.

(1)A relational database that serves as a repository of information uncovered during an extensive review of passenger and freight mode choice literature. This relational database forms essentially the core of the qualitative analysis component.

(2)Expert opinions on freight mode choice factors and policies obtained during a Delphi survey that can be viewed as charts or tables.

(3)Longitudinal data on modal utilizations and socioeconomic trends, incorporated as charts and tables, for undertaking baseline assessments and identifying trends.

(4)A mode choice model and data for freight mode choice forecasting.

The graphical user interface provides an intuitive and easy-to-use environment for accessing the different components of the DSS. Table 2.2 summarizes the qualitative and quantitative analyses that can be performed in the contexts of passenger and freight traffic.

Table 2.2Qualitative and quantitative analyses that can be performed using the DSS

Qualitative / Quantitative
Passenger /

• Assess the impact of various policies/trends on mode utilization
• Identify all policies/trends that have the desired directional impact on a specific mode

/

• View information on current mode utilization in Texas

Freight /

• Assess the impact of a various policies/trends on mode utilization
• Identify all policies/trends that have the desired directional impact on a specific mode
• Query the opinions of experts on the impact of various policies/trends on mode utilization

/

• Analyze modal and socioeconomic trends using interactive tables and charts
• Examine the impact of changes in a number of variables on intercounty mode shares

The interface is also designed to provide well-organized output displays. In the context of baseline assessment analysis, the output often has the form of a pivot table or a pivot chart. Hence, the user is not restricted to a precompiled format of the presented data. In addition, the embedded data tables can be easily exported to other spreadsheet applications for further analysis.

2.4Concluding Remarks

It is necessary to mention that the knowledge base included within this software, although substantial, is by no means exhaustive. There are also several regional and national modal sharedata sources that can be incorporated into this prototype version of the software. The design of the software provides the analyst with the flexibility to enhance the prototype by including additional literature and data sources. This DSS software tool can thus be continually updated with the latest research findings and data trends.

3. The Qualitative Analysis Tool

As was indicated in the previous chapter, the decision support system (DSS) incorporates a knowledge base of recent, published impacts of various factors on passenger and freight mode utilization. A factor was defined as a policy pertaining to a metropolitan area, state, or region, or a general development relating to the operation of the transportation system (e.g., technology changes). The qualitative analysis component of the DSS allows the analyst to access the knowledge base in two ways: The analyst can (a) conduct objective-oriented analysis or (b) perform a policy-oriented analysis. This chapter is organized as follows. The objective-oriented analysis component is discussed in Section 3.1, and the policy-oriented analysis component is discussed in Section 3.2. Section 3.3 provides some important concluding remarks on the qualitative analysis tool and its use.

3.1Objective-Oriented Analysis

The objective-oriented analysis component of the qualitativeanalysis tool allows the analyst to view possible factors and policies that can contribute toward the achievement of a selected objective. The objective is specified in terms of the desired directional impact on the mode share of any one the different modes supported by the software. As has already been mentioned, the DSS supports four passenger modes (i.e., drive-alone, shared-ride, transit, and nonmotorized) and four freight modes (i.e., truck, rail, water, and air). The software searches the underlying knowledgebase and returns a list of all factors that are known to produce the desired impact. The latter can include both policies available to the analyst to achieve the desired impact as well as developments (possibly beyond the control of the policymaker) that can produce the specified mode shifts. To facilitate the assimilation of the results, the exhaustive list of factors and policies supported by the software has been classified into broad categories called the primary factors (see Table 3.1). The interface sorts the results to the user-specified objective in terms of these primary factors.